Deep ground temperature field prediction method and device and storage medium

Abstract

The invention provides a deep ground temperature field prediction method and device and a storage medium, and the method comprises the following steps: equally dividing each logging temperature-resistivity data pair of a research region or an adjacent region into N segments, and carrying out the normalization processing of the resistivity of each layer segment; deducing the optimal correction temperature, the intrinsic normalized resistivity and the temperature correction coefficient of different well positions and different layer sections, constructing a data set through the optimal correction temperature, the intrinsic normalized resistivity and the temperature correction coefficient and the corresponding depth, carrying out regression analysis, and obtaining changes T0 (z), rhoNT0 (z) and alphaT0 (z) along with the depth respectively; performing resistivity inversion on the electromagnetic data volume in the research area, equally dividing the electromagnetic data volume into M sections, and normalizing the resistivity of different layer sections to be rho Ninv (x, z); based on the T0 (z), the rhoNT0 (z), the alphaT0 (z) and the rhoNinv (x, z), obtaining relation characterization between normalized inversion resistivity and temperature of different nodes of different underground layer sections of the research area, and predicting distribution characteristics of the underground space temperature field of the research area according to the relation characterization. According to the method, the macroscopic resistivity characteristics of the underground medium can be accurately converted into visual temperature field distribution, the practicability is high, and the prediction range is wide and deep.

Description

technical field [0001] The invention relates to the field of geothermal field prediction, in particular to a deep geothermal field prediction method, equipment and storage medium. Background technique [0002] Understanding temperature is one of the key characteristics of the Earth's interior determines our ability to investigate fundamental Earth science questions and apply geothermal problems. Therefore, it is extremely important to accurately estimate the temperature distribution characteristics of underground space as much as possible. [0003] Currently, temperature estimates of the Earth's interior are typically based on borehole temperature logs or heat flow gradient data. The former perform spatial interpolation based on temperature logs measured in several wells distributed irregularly on the surface, which often leads to considerable estimation errors. The establishment of the temperature model in the latter is based on the assumption of the stable state of heat ...

AI Technical Summary

Problems solved by technology

However, at present, the use of resistivity for temperature prediction is based on the use of pure empirical formulas, and its validity is assumed not to vary with spatial locati

Images